基于CGGA数据库构建的列线图模型预测胶质母细胞瘤患者预后分析  

A nomogram model based on CGGA database to predict the prognosis of glioblastoma patients

作　　者：郭社卫 甄英伟 林发 GUO Shewei;ZHEN Yingwei;LIN Fa(Department of Neurosurgery,the First Affiliated Hospital of Zhengzhou University,Zhengzhou,Henan 450000,China;Department of Neurosurgery,Beijing Tiantan Hospital,Capital Medical University,Beijing 100050,China)

机构地区：[1]郑州大学第一附属医院神经外科,河南郑州450000 [2]首都医科大学附属北京天坛医院神经外科,北京100050

出　　处：《中华神经外科疾病研究杂志》2024年第5期15-21,共7页Chinese Journal of Neurosurgical Disease Research

基　　金：国家重点研发计划“常见多发病防治研究”重点专项2021年度项目(2021YFC2501100)。

摘　　要：目的基于中国脑胶质瘤基因组图谱数据库(CGGA)资料分析,构建有效预测胶质母细胞瘤(GBM)患者预后的列线图模型,以期为临床治疗提供帮助。方法从CGGA数据库获取下载全基因转录组_693(mRNAseq_693)测序数据及临床数据,应用LASSO-COX回归分析影响因素及相关功能基因,将患者依据风险评分划分为高风险组、低风险组,对相关基因的功能注释并进行了基因本体(GO)和信号通路富集(KEGG)分析。构建列线图预测模型,以校准曲线评估列线图的性能。结果249例GBM患者中140例原发、109例复发,从23974个基因中筛选出237个基因升高(筛选标准:r/p>2且P<0.005),119个基因降低(筛选标准:r/p<0.5且P<0.005)。通过LASSOCOX降维分析筛选出9个候选基因(CPLX1、DPT、FAM225B、GNAS_AS1、GRM5、HAR1B、NGFR、RP11_403I13.4及RP11_498C9.13),并依据其相应的λ值来计算每位患者的RiskSocre评分,中位RiskSocre临界值为0.013。随着RiskSocre评分的增加,PRS、IDH突变状态、1p19q共缺失状态及9个候选基因表现出不对称分布特征。高危组复发占比、IDH野生占比、1p19q未缺失占比高于低危组(P<0.05)。Kaplan-Meier曲线表明,高危组患者的OS低于低危组患者(P<0.05)。GBM复发患者的RiskSocre评分显著增加,女性患者的RiskSocre评分略有增加;RiskSocre评分与年龄、术后放疗、术后化疗、IDH突变状态、1p19q共缺失状态、MGMTp启动子甲基化状态无相关性。GO分析表明,与RiskSocre评分最相关的生物学过程包括免疫应答,免疫应答调节和T细胞共刺激;KEGG分析表明,与RiskSocre评分最相关信号通路是T细胞受体信号通路,包括细胞粘附分子和抗原加工和呈递。GBM患者的(1年、2年、3年、5年和9年)肿瘤复发概率可通过个体化预测模型进行估计;校准曲线中的列线图和实际观测结果显示出令人满意的重叠,表明较佳的预测准确性。结论建立列线图模型,预测GBM患者的1年、2年、3�Objective To predict the prognosis of glioblastoma(GBM)patients based on the analysis of the Chinese Glioma Genome Atlas(CGGA)database data.Methods The whole gene transcriptome_693(mRNAseq_693)sequencing data and clinical data from CGGA database were acquired and downloaded.LASSO-COX regression was utilized to analyze the influencing factors and related functional genes.Patients were divided into the high-risk group and the low-risk group according to the risk score.Functional annotation of related genes as well as Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analysis were carried out.A nomogram prediction model was built to calibrate the efficacy of curves in evaluating the nomogram.Results Amidst the 249 patients with GBM,140 were primary while 109 were recurrent.237 genes were identified as elevated(screening criteria:r/p>2 and P<0.005)and 119 genes as decreased(screening criteria:r/p<0.5 and P<0.005)from 23974 genes.9 candidate genes(CPLX1,DPT,FAM225B,GNAS_AS1,GRM5,HAR1B,NGFR,RP11_403I13.4 and RP11_498C9.13)were selected by LASSO-COX analysis of dimensionality reduction,and the RiskSocre of each patient was calculated according to their correspondingλvalues with the median RiskSocre critical value being 0.013.With the increase of RiskSocre score,common characteristics of asymmetric distribution were displayed in PRS,IDH mutation state,1p19q co-deletion state and 9 candidate genes.The proportion of recurrence,IDH wild type and 1p19q non-deletion type in the high-risk group was upregulated compared with those in the low-risk group(P<0.05).Kaplan-Meier curve showed that the OS of high-risk patients was lower than that of low-risk patients(P<0.05).The RiskSocre of patients with recurrent GBM significantly increased while the RiskSocre of female patients slightly increased,and the RiskSocre was not correlated with age,postoperative radiotherapy,postoperative chemotherapy,IDH mutation status,1p19q co-deletion status,and the methylation status of MGMTp promoter.GO analysis indicated that the bi

关 键 词：胶质母细胞瘤 中国脑胶质瘤基因组图谱数据库 基因本体分析 信号通路富集分析 列线图模型 预后 

分 类 号：R739.41[医药卫生—肿瘤]